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Record W4388049731 · doi:10.12968/bjca.2023.0009

Do interventions targeting frailty improve outcomes after cardiac surgery? A systematic review

2023· review· en· W4388049731 on OpenAlexaff
Samantha Cook, Suzanne Fredericks, Souraya Sidani, Barbara Bailey, Shereli Soldevilla, Julie Sanders

Bibliographic record

VenueBritish Journal of Cardiac Nursing · 2023
Typereview
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsUniversity of TorontoToronto Metropolitan University
Fundersnot available
KeywordsMedicinePsychological interventionIntervention (counseling)Cardiac surgeryPhysical therapySystematic reviewMEDLINEIntensive care medicineGerontologySurgeryNursing

Abstract

fetched live from OpenAlex

Frail patients have poorer cardiac surgery outcomes. Interventions targeting frailty may improve surgical recovery. This study explored interventions that specifically target frailty in patients undergoing cardiac surgery. A systematic review was conducted, searching multiple electronic databases from January 2010 to May 2022. Studies applying an intervention targeting frailty (measured using a validated tool) in adults undergoing cardiac surgery were included. Data extraction and quality assessments were undertaken by two authors. From 2726 identified papers, five studies were included in the final review. Studies varied in their definitions of frailty, methods and intervention components. All included an exercise component, but these varied in frequency, length and content. Three studies reported an improvement in frailty. This review identified that there is some evidence that frailty is improved after an exercise intervention. Further research should focus on the multifaceted nature of frailty, the degree to which frailty is reversed by interventions and the effectiveness of such interventions specifically for women.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesMeta-epidemiology (broad)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.371
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0150.018
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.062
GPT teacher head0.382
Teacher spread0.320 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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